Immune checkpoint inhibitor rechallenge in patients who previously experienced immune-related inflammatory arthritis: a multicentre observational study
Bibliographic record
Abstract
OBJECTIVE: Another course of immune checkpoint inhibitors (ICIs) is often considered in patients with cancer progression and previous immune-related adverse events, including inflammatory arthritis (ICI-IA), but there are limited data regarding safety of ICI rechallenge in this setting. We aimed to assess the rate and clinical features associated with ICI-IA flare/recurrence on ICI rechallenge. METHODS: We conducted a multicentre observational study including cancer patients with ICI-IA who started a second course of ICI more than 3 months after ICI discontinuation in four French university hospitals. Primary outcome was the frequency of ICI flare/recurrence after ICI rechallenge. RESULTS: Twenty-three patients were included. At the time of ICI rechallenge, 18 patients reported no symptoms of ICI-IA (78%) and 5 had grade 1 (22%), 11 patients (48%) were not receiving any ICI-IA treatment, 11 (48%) were still on prednisone, 2 (9%) were on conventional synthetic disease-modifying antirheumatic drugs and 1 (4%) on anti-IL-6. ICI-IA flare/recurrence occurred in 12 patients (52%) with a median time of 1 month after ICI rechallenge. ICI-IA phenotype, disease activity and ICI-IA treatment at the time of ICI rechallenge did not differ according to ICI-IA flare/recurrence status. CONCLUSION: In this first observational study of ICI-IA patients rechallenged with ICI, about half of the patients experienced ICI-IA flare/recurrence with a similar phenotype but occurring earlier than the initial ICI-IA, warranting close monitoring during the first month of retreatment. Risk of flare did not differ according to baseline immunosuppressive treatment at the time of rechallenge.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".